Technical Field
This disclosure relates generally to the field of automated music analysis. More particularly, it relates to using unsupervised learning of musical pieces and computer creation of music based on the unsupervised learning.
Background of the Related Art
Computer aided musical composition is not new. There have been efforts dating from the 1950s using Markov chains to generate music using computers. There has been much work since that time. Neural networks have been used in more recent work to learn musical features in human written music as part of the process by which the computer learns to write music. During the learning, the neural networks have operated in either a supervised or an unsupervised mode. In a supervised mode, the inputs and outputs are controlled by a supervising human user who guides the computer to desired outputs. In an unsupervised mode, the computer does not have human guidance. The computer learns the patterns and features of the music, and organizes its learning into a form which can be used to generate music.
While efforts to provide computer aided musical composition have been many, the actual musical output has been mixed in comparison to music written by a human composer. Further, though the computer output has rarely matched the musical works of a skilled human composer, the effort on the part of highly skilled and intelligent computer scientists has been great. The training needed both to produce skilled computer scientists in the first place, and then for these skilled individuals to prepare the computer aided music systems to produce music in terms of time is considerable. Many systems require a volume of preexisting music data to analyze as well as a detailed set of rules concerning music theory. Typically, the inputs and desired output of these systems has been expressed in non-musical and non-intuitive forms, making them incomprehensible to a layman. Despite over sixty years of effort, current methods have fallen short.
It would be highly desirable to provide computer aided music composition which is accessible to an untrained, non-technical, non-musician, that is, an average person, which provides real time results.